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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

American Meteorological Society (AMS) - The Modern Era Retrospective-Analysis for Research and Applications (MERRA) Data and Accessibility

The AM Short Course on The Modern Era Retrospective-analysis for Research and Applications (MERRA) data and accessibility will be held on January 11, 2009 preceding the 89th Annual Meeting in Phoenix, Arizona. Preliminary programs, registration, hotel, and general information will be posted on the AMS Web site in mid-September 2008. Retrospective-analyses (or reanalyses) have been established as an important tool in weather and climate research over the last decade. As computer power increases, the data assimilation and modeling systems improve and become more advanced, the input data quality increases and so reanalyses become more reliable. In 2008, NASA Global Modeling and Assimilation Office began producing a new reanalysis called the Modem Era Retrospective-analysis for Research and Applications (MERRA). The initial data from the reanalysis has been made available to the community and should be complete through 30 years (1979-present) by Fall of 2009. MERRA has taken advantage of the advancement of computing resources to provide users more data than previously available. The native spatial resolution is nominally 1/2 degrees and the surface two dimensional data are one hourly frequency. In addition to the meteorological analysis data, complete mass, energy and momentum budget data and also stratospheric data are provided. The eventual data holdings will exceed 150Tb. In order to facilitate user accessibility to the data, it will be stored in online hard drives (not tape storage) and available through several portals. Subsetting tools will also be available to allow users to tailor their data requests. The goals of this short course are to provide hands on users of reanalyses instruction on MERRA systems and also interactive experience with the online data and access tools. The course is intended for students and research scientists who will be actively interested in accessing and applying MERRA data in their weather, climate or applications work. The course has three parts. There will be an overview of the MERRA system, the validation of the system and the native data format. Second, Instructors will provide examples of weather and climate data analysis using various software packages (primarily GrADS) as well as the online access tools for subsetting and download, as well as visualization (e.g. Giovanni and Google Earth). This will also include examples on changing the data format to fit user's preferences and also to regrid the data for comparisons to other reanalyses and observational data. Lastly, there will he time set aside for participants to have hands on access to the data and software while interacting with the instructors and other developers. The course convener is Dr. Michael Bosilovich, NASA GSFC Global Modeling and Assimilation Office (GMAO). He will be joined by several GMAO, Goddard Earth Science Data and information Services Center (GES DISC) and Software Integration and Visualization Office (SIVO) staff.

daSilva, Arlindo↗
NASA NTRS1994

NSSDC provides network access to key data via NDADS

The National Space Science Data Center (NSSDC) is making a growing fraction of its most customer-desirable data electronically accessible via both the local and wide area networks. NSSDC is witnessing a great increase in its data dissemination owing to this network accessibility. To provide its customers the best data accessibility, the NSSDC makes data available from a nearline, mass storage system, the NSSDC Data Archive and Dissemination Service (NDADS). The NDADS, the initial version was made available in January 1992, is a customized system of hardware and software that provides users access to the nearline data via ANONYMOUS FTP, an e-mail interface (ARMS), and a C-based software library. In January 1992, the NDADS registered 416 requests for 1,957 files. By December of 1994, NDADS had been populated with 800 gigabytes of electronically accessible data and had registered 1458 requests for 20,887 files. In this report we describe the NDADS system, both hardware and software. Later in the report, we discuss some of the lessons that were learned as a result of operating NDADS, particularly in the area of ingest and dissemination.

Behnke, Jeanne↗
DOE OSTI2021

Accessing protected data by a high-performance computing cluster

A data protection system is provided that allows applications to access protected data in a way that restricts applications from outputting to unauthorized targets any unprotected data derived from the protected data and that ensures that the applications do not have access to a key that allows access to the unprotected data. The data protection system provides a policy server that may execute on a service node of a high performance computing system and a data encryption process that may execute on each compute node that is allocated to an application or batch job. The policy server maintains policies of entities specifying access control for protected data. The data encryption process generates a secure execution environment for an application process and interfaces with the policy server to retrieve keys for decrypting protected data in accordance with a policy, and it decrypts and provides the decrypted data to the application process.

Barnes, Peter↗
DOE OSTI2023

Effectiveness and predictability of in-network storage cache for Scientific Workflows

Large scientific collaborations often have multiple scientists accessing the same set of files while doing different analyses, which create repeated accesses to the large amounts of shared data located far away. These data accesses have long latency due to distance and occupy the limited bandwidth available over the wide-area network. To reduce the wide-area network traffic and the data access latency, regional data storage caches have been installed as a new networking service. To study the effectiveness of such a cache system in scientific applications, we examine the Southern California Petabyte Scale Cache for a high-energy physics experiment. By examining about 3TB of operational logs, we show that this cache removed 67.6% of file requests from the wide-area network and reduced the traffic volume on wide-area network by 12. 3TB (or 35.4%) an average day. The reduction in the traffic volume (35.4%) is less than the reduction in file counts (67.6%) because the larger files are less likely to be reused. Due to this difference in data access patterns, the cache system has implemented a policy to avoid evicting smaller files when processing larger files. We also build a machine learning model to study the predictability of the cache behavior. Tests show that this model is able to accurately predict the cache accesses, cache misses, and network throughput, making the model useful for future studies on resource provisioning and planning.

Sim, Caitlin↗
NASA NTRS1984

Advanced communications technologies for image processing

It is essential for image analysts to have the capability to link to remote facilities as a means of accessing both data bases and high-speed processors. This can increase productivity through enhanced data access and minimization of delays. New technology is emerging to provide the high communication data rates needed in image processing. These developments include multi-user sharing of high bandwidth (60 megabits per second) Time Division Multiple Access (TDMA) satellite links, low-cost satellite ground stations, and high speed adaptive quadrature modems that allow 9600 bit per second communications over voice-grade telephone lines.

Likens, W. C.↗
NASA NTRS2017

Online Visualization and Value Added Services of MERRA-2 Data at GES DISC

NASA climate reanalysis datasets from MERRA-2, distributed at the Goddard Earth Sciences Data and Information Services Center (GES DISC), have been used in broad research areas, such as climate variations, extreme weather, agriculture, renewable energy, and air quality, etc. The datasets contain numerous variables for atmosphere, land, and ocean, grouped into 95 products. The total archived volume is approximately 337 TB ( approximately 562K files) at the end of October 2017. Due to the large number of products and files, and large data volumes, it may be a challenge for a user to find and download the data of interest. The support team at GES DISC, working closely with the MERRA-2 science team, has created and is continuing to work on value added data services to best meet the needs of a broad user community. This presentation, using aerosol over Asia Monsoon as an example, provides an overview of the MERRA-2 data services at GES DISC, including: How to find the data? How many data access methods are provided? What are the best data access methods for me? How do download the subsetted (parameter, spatial, temporal) data and save in preferred spatial resolution and data format? How to visualize and explore the data online? In addition, we introduce a future online analytic tool designed for supporting application research, focusing on long-term hourly time-series data access and analysis.

Shen, Suhung↗
NASA NTRS2026

PERSIANN-Unet: A Global Deep Learning Framework for Near-Real-Time Precipitation Estimation Using Infrared Data

Access to high-quality, high-resolution, near-real-time precipitation data is essential for hydrological and meteorological research and disaster mitigation. Traditional tools such as rain gauges and radar networks, though effective, have limitations, including sparse coverage in remote areas and high operational costs. Satellite data, with its global coverage and high spatial and temporal resolutions, mitigates limitations in coverage. Satellite precipitation products like Hydro Estimator (HE), Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) utilize both geosynchronous thermal infrared (IR) and passive microwave (PMW) data in their operation. PMW sensors offer detailed atmospheric profiles but suffer from higher latency, whereas IR sensors provide lower latency but only capture cloud-top information. Despite this constraint, IR data remains attractive for low-latency precipitation estimation. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have further improved satellite precipitation retrievals. This study introduces PERSIANN-Unet (PUnet or PERSIANN V3), a quasi-global algorithm covering 60°N–60°S that combines IR data, monthly climatology, and the UNet architecture to produce half-hourly precipitation estimates at 0.04° resolution. The product is evaluated against HE, IMERG, and PDIR-Now for 2022–2023. Results show that PUnet closely matches its training target, IMERG V07 Final, at the global scale, and performance is further evaluated against Stage IV as a reference over CONUS. Training PUnet on IMERG (2016–2021) leverages a high-quality, integrated PMW IR-gauge precipitation product while developing an IR-based framework not reliant on PMW availability. By operating on a single global image, PUnet avoids tile partitioning and blending steps, reducing edge discontinuities, and produces more spatially consistent precipitation fields across hemispheres.

Phu Nguyen↗
DOE OSTI2023

A use-case-driven approach for demonstrating the added value of digitalisation in wind energy

Digitalisation is one of the key drivers for reducing the costs and risks of wind energy. When considering whether to embark on a digitalisation initiative, two key questions arise. The first is what business or operational opportunities might feasibly be addressed and the second is which of the many potential aspects of digitalisation are relevant to those opportunities. In this work, we show how these questions can be answered with a use-case-driven approach, based around a survey aiming to collect and collate the main "pain points" (or everyday challenges) of people in the wind energy sector. Although the relatively low number of participants of the survey (46) means that the results should only be used indicatively, it is still possible to make some general recommendations for priorities for digitalisation efforts in the wind energy sector. Firstly, digitalisation efforts should focus both on supporting people carrying out cross-lifecycle tasks, in particular sharing data, managing data, undertaking general data analyses and accessing data. Tools to do this should deal with varying data formats and naming conventions, make metadata more accessible, define data and metadata standards, make more data publicly available and improve the quality of data. Secondly, efforts should also focus on supporting people in the wind farm operational phase, in particular with failure detection, fault diagnosis, failure rate modelling and predictive maintenance. Solutions to do this should focus on accessible and validated tools for fault detection, cloud or other data pipeline solutions for SCADA data and tools for exhaustive data documentation. Finally, digitalisation efforts should focus on better communicating and helping people become aware of existing solutions and tools, as well as on helping people to exert a stronger influence on possible solutions.

17 WIND ENERGY↗
NASA NTRS1981

Survey of Federal, National, and International standards applicable to the NASA applications data services

An applications data service (ADS) was developed to meet the challenges in the data access and integration. The ADS provides a common service to locate and access applications data electronically and integrate the cross correlative data sets required by multiple users. Its catalog and network services increase data visibility as well as provide the data in a more rapid manner and a usable form.

Kuch, T.↗
NASA NTRS1984

Observational Requirements and Measurement Systems Concepts

Six philosophical elements that a measurement strategy for dynamic qualities should contain are: systemic global observations; nested coverage; continuous upgrading of observational capability and testing of promising instrument concepts; orbit considerations; quality control: data validity and management; and data interpretation. The criteria for determining an observational program should include the following: significance of the primary scientific questions, technical readiness; potential of undeveloped techniques, engineering and economic feasibility; and data access and data systems.

Source record↗
NASA NTRS1991

WetNet operations

WetNet is an interdisciplinary Earth science data analysis and research project with an emphasis on the study of the global hydrological cycle. The project goals are to facilitate scientific discussion, collaboration, and interaction among a selected group of investigators by providing data access and data analysis software on a personal computer. The WetNet system fulfills some of the functionality of a prototype Product Generation System (PGS), Data Archive and Distribution System (DADS), and Information Management System for the Distributed Active Archive Center. The PGS functionality is satisfied in WetNet by processing the Special Sensor Microwave/Imager (SSM/I) data into a standard format (McIDAS) data sets and generating geophysical parameter Level II browse data sets. The DADS functionality is fulfilled when the data sets are archived on magneto optical cartridges and distributed to the WetNet investigators. The WetNet data sets on the magneto optical cartridges contain the complete WetNet processing, catalogue, and menu software in addition to SSM/I orbit data for the respective two week time period.

Goodman, H. Michael↗
NASA NTRS2005

Strawman Philosophical Guide for Developing International Network of GPM GV Sites

The creation of an international network of ground validation (GV) sites that will support the Global Precipitation Measurement (GPM) Mission's international science programme will require detailed planning of mechanisms for exchanging technical information, GV data products, and scientific results. An important component of the planning will be the philosophical guide under which the network will grow and emerge as a successful element of the GPM Mission. This philosophical guide should be able to serve the mission in developing scientific pathways for ground validation research which will ensure the highest possible quality measurement record of global precipitation products. The philosophical issues, in this regard, partly stem from the financial architecture under which the GV network will be developed, i.e., each participating country will provide its own financial support through committed institutions -- regardless of whether a national or international space agency is involved.At the 1st International GPM Ground Validation Workshop held in Abingdon, UK in November-2003, most of the basic tenants behind the development of the international GV network were identified and discussed. Therefore, with this progress in mind, this presentation is intended to put forth a strawman philosophical guide supporting the development of the international network of GPM GV sites, noting that the initial progress has been reported in the Proceedings of the 1st International GPM GV Workshop -- available online. The central philosophical issues themselves, all flow from the fact that each participating institution can only bring to the table, GV facilities and scientific personnel that are affordable to the sanctioning (funding) national agency (be that a research, research-support, or operational agency). This situation imposes on the network, heterogeneity in the measuring sensors, data collection periods, data collection procedures, data latencies, and data reporting capabilities. Therefore, in order for the network to be effective in supporting the central scientific goals of the GPM mission, there must be a basic agreed upon doctrine under which the network participants function vis-a-vis: (1) an overriding set of general scientific requirements, (2) a minimal set of policies governing the free flow of GV data between the scientific participants, (3) a few basic definitions concerning the prioritization of measurements and their respective value to the mission, (4) a few basic procedures concerning data formats, data reporting procedures, data access, and data archiving, and (5) a simple means to differentiate GV sites according to their level of effort and ability to perform near real-time data acquisition - data reporting tasks. Most important, in case they choose to operate as a near real-time data collection-data distribution site, they would be expected to operate under a fairly narrowly defined protocol needed to ensure smooth GV support operations. This presentation will suggest measures responsive to items (1) - (5) from which to proceed,. In addition, this presentation will seek to stimulate discussion and debate concerning how much heterogeneity is tolerable within the eventual GV site network, given that the any individual GV site can only be considered scientifically useful if it supports the achievement of the central GPM Mission goals. Only ground validation research that has a direct connection to the space mission should be considered justifiable given the overarching scientific goals of the mission. Therefore each site will have to seek some level of accommodation to what the GPM Mission requires in the way of retrieval error characterization, retrieval error detection and reporting, and generation of GV data products that support assessment and improvement of the mission's standard precipitation retrieval algorithms. These are all important scientific issues that will be best resolved in open scientific debate.

Smith, Eric A.↗
NASA NTRS2013

Remote Data Exploration with the Interactive Data Language (IDL)

A difficulty for many NASA researchers is that often the data to analyze is located remotely from the scientist and the data is too large to transfer for local analysis. Researchers have developed the Data Access Protocol (DAP) for accessing remote data. Presently one can use DAP from within IDL, but the IDL-DAP interface is both limited and cumbersome. A more powerful and user-friendly interface to DAP for IDL has been developed. Users are able to browse remote data sets graphically, select partial data to retrieve, import that data and make customized plots, and have an interactive IDL command line session simultaneous with the remote visualization. All of these IDL-DAP tools are usable easily and seamlessly for any IDL user. IDL and DAP are both widely used in science, but were not easily used together. The IDL DAP bindings were incomplete and had numerous bugs that prevented their serious use. For example, the existing bindings did not read DAP Grid data, which is the organization of nearly all NASA datasets currently served via DAP. This project uniquely provides a fully featured, user-friendly interface to DAP from IDL, both from the command line and a GUI application. The DAP Explorer GUI application makes browsing a dataset more user-friendly, while also providing the capability to run user-defined functions on specified data. Methods for running remote functions on the DAP server were investigated, and a technique for accomplishing this task was decided upon.

Galloy, Michael↗
NASA NTRS2019

GeoNEX: A Cloud Gateway for Near Real-time Processing of Geostationary Satellite Products

The emergence of a new generation of geostationary satellite sensors provides land andatmosphere monitoring capabilities similar to MODIS and VIIRS with far greater temporal resolution (5-15 minutes). However, processing such large volume, highly dynamic datasets requires computing capabilities that (1) better support data access and knowledge discovery for scientists; (2) provide resources to enable real-time processing for emergency response (wildfire, smoke, dust, etc.); and (3) provide reliable and scalable services for the broader user community. This paper presents an implementation of GeoNEX (Geostationary NASA-NOAA Earth Exchange) services that integrate scientific algorithms with Amazon Web Services (AWS) to provide near realtime monitoring (~5 minute latency) capability in a hybrid cloud-computing environment. It offers a user-friendly, manageable and extendable interface and benefits from the scalability provided by Amazon Web Services. Four use cases are presented to illustrate how to (1) search and access geostationary data; (2) configure computing infrastructure to enable near real-time processing; (3) disseminate and utilize research results, visualizations, and animations to concurrent users; and (4) use a Jupyter Notebook-like interface for data exploration and rapid prototyping. As an example of (3), the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) was implemented on GOES-16 and -17 data to produce an active fire map every 5 minutes over the conterminous US. Details of the implementation strategies, architectures, and challenges of the use cases are discussed.

GeoNEX↗
NASA NTRSDate not supplied

TPSAS-NF1676L-16833-DND

Semantic Infrastructure is central to realizing the first goal of the ASDC's Strategic Plan: expanding the ASDC's customer base by improving access to ASDC data. ASDC data comprises a widely heterogeneous set of complex products which presents two significant challenges in data access: Helping customers discover, among many available options, the most suitable data products for their purpose; and Guiding customers to easily and appropriately use products. Data products differ significantly in terms of how the data was collected and processed, even with similar subject matter. Understanding differences is critical to using data effectively. To reach a broader customer range, the ASDC must provide prospective users with enough information to quickly and meaningfully compare and evaluate data products. Data formats and structures also differ among products. Applications displaying and analyzing data need access to federated and semantically disambiguated data. Semantic technologies offer functionality for addressing this issue. Ontologies can provide robust, stable domain models serving as common schema for discovering, evaluating, comparing, and integrating data from disparate products. Reasoning engines and triple stores can leverage ontologies to support intelligent search applications allowing users to discover, query, retrieve, and easily reformat data from a broad spectrum of sources.

Beth Huffer↗
NASA NTRSDate not supplied

Why We Do What We Do: Data Reuse, Open Access and Privacy in Data Management at the Life Sciences Data Archive

As custodians of the unique and irreplaceable collections of human subject research data generated by the Human Research Program and its predecessors throughout the agency’s history, the Life Sciences Data Archive (LSDA) is charged with protecting participants’ privacy and implementing their consent decisions as it provides retrospective data for use in new studies. This active, stewardship-focused approach to data management and preservation shapes the products that LSDA provides to researchers and the responsibilities of researchers in using the data and publishing their results. This presentation reviews how federal and agency mandates shape LSDA’s data management procedures and expectations for researchers. Topics covered will include LSDA’s movement towards implementation of the FAIR (Findable, Accessible, Interoperable, Reusable) principles and the archive’s evolving data management practices; collaboration between LSDA and the Lifetime Surveillance of Astronaut Health (LSAH) project (the repository of astronaut medical data); LSDA’s response to the challenges of performing its stewardship role and maintaining trust given the public profiles of the subjects whose data it preserves; and the ever-increasing challenges to expectations of subject privacy stemming from the growing power and ubiquity of data analysis and aggregation tools.

data management↗
NASA NTRS2006

The Virtual Space Physics Observatory: Quick Access to Data and Tools

The Virtual Space Physics Observatory (VSPO; see http://vspo.gsfc.nasa.gov) has grown to provide a way to find and access about 375 data products and services from over 100 spacecraft/observatories in space and solar physics. The datasets are mainly chosen to be the most requested, and include most of the publicly available data products from operating NASA Heliophysics spacecraft as well as from solar observatories measuring across the frequency spectrum. Service links include a "quick orbits" page that uses SSCWeb Web Services to provide a rapid answer to questions such as "What spacecraft were in orbit in July 1992?" and "Where were Geotail, Cluster, and Polar on 2 June 2001?" These queries are linked back to the data search page. The VSPO interface provides many ways of looking for data based on terms used in a registry of resources using the SPASE Data Model that will be the standard for Heliophysics Virtual Observatories. VSPO itself is accessible via an API that allows other applications to use it as a Web Service; this has been implemented in one instance using the ViSBARD visualization program. The VSPO will become part of the Space Physics Data Facility, and will continue to expand its access to data. A challenge for all VOs will be to provide uniform access to data at the variable level, and we will be addressing this question in a number of ways.

Cornwell, Carl↗
NASA NTRS2025

Why We Do What We Do: Data Reuse, Open Access, and Privacy in Data Management at the Life Sciences Data Archive

As custodian of the unique and irreplaceable collections of human subject research data generated by the Human Research Program and its predecessors throughout the agency’s history, the Life Sciences Data Archive (LSDA) is charged with protecting participants’ privacy and implementing their consent decisions as it provides retrospective data for use in new studies. This active, stewardship-focused approach to data management and preservation shapes the products that LSDA provides to researchers and the responsibilities of researchers in using the data and publishing their results. This presentation reviews how federal and agency mandates shape LSDA’s data management procedures and expectations for researchers. Topics covered will include LSDA’s movement towards implementation of the FAIR (Findable, Accessible, Interoperable, Reusable) principles and how the archive’s evolving data management practices support FAIR-ness; collaboration between LSDA and the Lifetime Surveillance of Astronaut Health (LSAH) project (the repository of astronaut medical data); LSDA’s response to the challenges of performing its stewardship role and maintaining trust given the public profiles of the subjects whose data it preserves; and the ever-increasing challenges to expectations of subject privacy stemming from the growing power and ubiquity of of data analysis and aggregation tools.

Data↗